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{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T15:25:45Z","timestamp":1703085945879},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T00:00:00Z","timestamp":1674777600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T00:00:00Z","timestamp":1674777600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"National Academies Keck Futures Initiative","award":["NAKFI CB4"]},{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","award":["HR0011-16-2-0019"]},{"name":"Christopher Family Foundation"},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R01GM117467"]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Barcode-based tracking of individuals is revolutionizing animal behavior studies, but further progress hinges on whether in addition to determining an individual\u2019s location, specific behaviors can be identified and monitored. We achieve this goal using information from the barcodes to identify tightly bounded image regions that potentially show the behavior of interest. These image regions are then analyzed with convolutional neural networks to verify that the behavior occurred. When applied to a challenging test case, detecting social liquid transfer (trophallaxis) in the honey bee hive, this approach yielded a 67% higher sensitivity and an 11% lower error rate than the best detector for honey bee trophallaxis so far. We were furthermore able to automatically detect whether a bee donates or receives liquid, which previously required manual observations. By applying our trophallaxis detector to recordings from three honey bee colonies and performing simulations, we discovered that liquid exchanges among bees generate two distinct social networks with different transmission capabilities. Finally, we demonstrate that our approach generalizes to detecting other specific behaviors. We envision that its broad application will enable automatic, high-resolution behavioral studies that address a broad range of previously intractable questions in evolutionary biology, ethology, neuroscience, and molecular biology.<\/jats:p>","DOI":"10.1038\/s41598-022-26825-4","type":"journal-article","created":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T13:03:50Z","timestamp":1674824630000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior"],"prefix":"10.1038","volume":"13","author":[{"given":"Tim","family":"Gernat","sequence":"first","affiliation":[]},{"given":"Tobias","family":"Jagla","sequence":"additional","affiliation":[]},{"given":"Beryl M.","family":"Jones","sequence":"additional","affiliation":[]},{"given":"Martin","family":"Middendorf","sequence":"additional","affiliation":[]},{"given":"Gene E.","family":"Robinson","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,27]]},"reference":[{"key":"26825_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/fevo.2015.00103","volume":"3","author":"F Wario","year":"2015","unstructured":"Wario, F., Wild, B., Couvillon, M. J., Rojas, R. & Landgraf, T. Automatic methods for long-term tracking and the detection and decoding of communication dances in honeybees. Front. Ecol. Evol. 3, 1\u201314 (2015).","journal-title":"Front. Ecol. Evol."},{"key":"26825_CR2","doi-asserted-b
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